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A R T I F I C I A L
I N T E L L I G E N C E
This Photo by Unknown author is licensed under CC BY.
K A S H A F N A
Z
B A T C H 1 8
R O L L # 0 2 5
C O M P U T E
R V I S I O N
COMPUTER VISIO
N
• Computer vision is a field
of artificial intelligence that
trains computers to interpret
and understand the visual
world. Using digital images
from cameras and videos
and deep learning models,
machines can accurately
identify and classify objects —
and then react to what they
“see.”
COMPUTER VISION
History of computer vision
• Early experiments in
computer vision took place in
the 1950s, using some of the
first neural networks to detect
the edges of an object and to
sort simple objects into
categories like circles and
squares.
History of computer vision
• In the 1970s, the first
commercial use of computer
vision interpreted typed or
handwritten text using optical
character recognition.
C O M P U T E
R V I S I O N
I N
T O D A Y ’ S
W O R L D
Computer
vision in
today’s world
• From recognizing faces to
processing the live action of
a football game, computer
vision rivals and surpasses
human visual abilities in
many areas.
How computer
vision works
• Computer vision works in three basic steps:
• Acquiring an image
• Images, even large sets, can be acquired in real-time
through video, photos or 3D technology for analysis
• Processing the image
• Ep learning models automate much of this process, but
the models are often trained by first being fed thousands
of labeled or pre-identified images.
• Understanding the image
• The final step is the interpretative step, where an object
is identified or classified.
• .
Today’s AI system
• Today’s AI systems can go a step further and
take actions based on an understanding of the
image. There are many types of computer
vision that are used in different ways:
• Image segmentation partitions an image into
multiple regions or pieces to be examined
separately.
• Object detection identifies a specific object in
an image. Advanced object detection
recognizes many objects in a single image: a
football field, an offensive player, a defensive
player, a ball and so on. These models use an
X,Y coordinate to create a bounding box and
identify everything inside the box.
This Photo by Unknown author is licensed under CC BY-SA.
Today’s AI
• Facial recognition is an advanced type of object
detection that not only recognizes a human face
in an image, but identifies a specific individual.
• Edge detection is a technique used to identify
the outside edge of an object or landscape to
better identify what is in the image.
• Pattern detection is a process of recognizing
repeated shapes, colors and other visual
indicators in images.
• Image classification groups images into
different categories.
• Feature matching is a type of pattern detection
that matches similarities in images to help
classify them.
This Photo by Unknown author is licensed under CC BY-ND.
T H A N K
Y O U

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AI Computer vision

  • 1. A R T I F I C I A L I N T E L L I G E N C E This Photo by Unknown author is licensed under CC BY.
  • 2. K A S H A F N A Z B A T C H 1 8 R O L L # 0 2 5
  • 3. C O M P U T E R V I S I O N
  • 4. COMPUTER VISIO N • Computer vision is a field of artificial intelligence that trains computers to interpret and understand the visual world. Using digital images from cameras and videos and deep learning models, machines can accurately identify and classify objects — and then react to what they “see.” COMPUTER VISION
  • 5. History of computer vision • Early experiments in computer vision took place in the 1950s, using some of the first neural networks to detect the edges of an object and to sort simple objects into categories like circles and squares.
  • 6. History of computer vision • In the 1970s, the first commercial use of computer vision interpreted typed or handwritten text using optical character recognition.
  • 7. C O M P U T E R V I S I O N I N T O D A Y ’ S W O R L D
  • 8. Computer vision in today’s world • From recognizing faces to processing the live action of a football game, computer vision rivals and surpasses human visual abilities in many areas.
  • 9. How computer vision works • Computer vision works in three basic steps: • Acquiring an image • Images, even large sets, can be acquired in real-time through video, photos or 3D technology for analysis • Processing the image • Ep learning models automate much of this process, but the models are often trained by first being fed thousands of labeled or pre-identified images. • Understanding the image • The final step is the interpretative step, where an object is identified or classified. • .
  • 10. Today’s AI system • Today’s AI systems can go a step further and take actions based on an understanding of the image. There are many types of computer vision that are used in different ways: • Image segmentation partitions an image into multiple regions or pieces to be examined separately. • Object detection identifies a specific object in an image. Advanced object detection recognizes many objects in a single image: a football field, an offensive player, a defensive player, a ball and so on. These models use an X,Y coordinate to create a bounding box and identify everything inside the box. This Photo by Unknown author is licensed under CC BY-SA.
  • 11. Today’s AI • Facial recognition is an advanced type of object detection that not only recognizes a human face in an image, but identifies a specific individual. • Edge detection is a technique used to identify the outside edge of an object or landscape to better identify what is in the image. • Pattern detection is a process of recognizing repeated shapes, colors and other visual indicators in images. • Image classification groups images into different categories. • Feature matching is a type of pattern detection that matches similarities in images to help classify them. This Photo by Unknown author is licensed under CC BY-ND.
  • 12. T H A N K Y O U